Always the Ideal? Exploring the Risks of Refugee Participation in Research
Bibliographic record
Abstract
Researchers in humanitarian settings increasingly encourage refugees and internally displaced persons (IDPs) to participate within broader research processes, beyond solely providing data. However, efforts to increase participation in research may be tokenistic, complicated by the challenges present in humanitarian settings. The assumption that more participation is always good has meant sometimes limited reflection occurs on the challenges associated with such participation. This study explores the possibilities and realities for refugee and IDP participation in research based on interviews with practitioners and academics who conduct participatory research with refugees and IDPs. It discusses lack of consensus in defining participation and explores five risks of participation that challenge the assumption that participation is always desirable and appropriate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.385 | 0.358 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.102 |
| Scholarly communication | 0.027 | 0.035 |
| Open science | 0.004 | 0.038 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".